Enhancing Bidirectional Encoder Representations From Transformers (BERT) With Frame Semantics to Extract Clinically Relevant Information From German Mammography Reports: Algorithm Development and Validation

This study demonstrates that frame semantics provides a robust and interpretable framework for automating structured reporting. By leveraging frame semantics, the approach enables customizable information extraction and supports generalization to diverse radiological domains and clinical contexts with additional annotation efforts. Furthermore, the BERT-based model architecture allows for efficient, on-premise deployment, ensuring data privacy. Future research should focus on validating the model's generalizability across external datasets and different report types to ensure its broader applicability in clinical practice.